{"title":"RoboCA3T：受机器人启发的计算机辅助自闭症适应疗法，通过学习和计算创新提高联合注意力和模仿能力","authors":"Zunera Zahid, Sara Ali, Shehriyar Shariq, Yasar Ayaz, Noman Naseer, Irum Yaseen","doi":"10.1111/jcal.12990","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>This study presents a Robot-Inspired Computer-Assisted Adaptive Autism Therapy (RoboCA<sup>3</sup>T) focusing on improving joint attention and imitation skills of children with autism spectrum disorder (ASD). By harnessing the inherent affinity of children with ASD for robots and technology, RoboCA<sup>3</sup>T offers a therapeutic environment designed to maximise engagement and facilitate effective skill development. It harnesses the advantages of Robot-Assisted Therapies (RATs) by employing robot avatars and integrating them with Computer-Assisted Therapies (CATs) within a web-based solution. The integration of automatic gaze and pose detection algorithms within RoboCA<sup>3</sup>T addresses the challenge posed by potential human error and observation bias in assessing the child's progress, thereby ensuring accurate results. This research responds to the need for more effective, technology driven therapies for autism, filling gaps in existing methods.</p>\n </section>\n \n <section>\n \n <h3> Objectives</h3>\n \n <p>The primary goal of this research is to create a robot inspired computer assisted adaptive autism therapy that maximises engagement and enhances joint attention and imitation skills.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>The study involves 11 ASD children with 30 sessions (divided into two halves) per module over eight months, comprising 660 experimental trials, 110 familiarizations, and 110 follow-up sessions. The joint attention module evaluates the subject's gaze pattern using WebGazer for gaze detection in response to four least-to-most robot-generated cues. The imitation module utilises robot-generated pose for comparing subjects' imitated actions using Tensorflow Lite for pose estimation.</p>\n </section>\n \n <section>\n \n <h3> Results and Conclusions</h3>\n \n <p>The effectiveness of therapy was substantiated by comparing Childhood Autism Rating Scale (CARS) scores before and after intervention. Significant improvements were noted between the first and second therapy halves, validated by Wilcoxon signed-rank tests (<i>p</i> < 0.01) and spearman's correlation analysis, reinforcing the observed improvements in joint attention and imitation skills.</p>\n </section>\n </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"40 5","pages":"2031-2048"},"PeriodicalIF":5.1000,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"RoboCA3T: A Robot-Inspired Computer-Assisted adaptive autism therapy for improving joint attention and imitation skills through learning and computing innovations\",\"authors\":\"Zunera Zahid, Sara Ali, Shehriyar Shariq, Yasar Ayaz, Noman Naseer, Irum Yaseen\",\"doi\":\"10.1111/jcal.12990\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>This study presents a Robot-Inspired Computer-Assisted Adaptive Autism Therapy (RoboCA<sup>3</sup>T) focusing on improving joint attention and imitation skills of children with autism spectrum disorder (ASD). By harnessing the inherent affinity of children with ASD for robots and technology, RoboCA<sup>3</sup>T offers a therapeutic environment designed to maximise engagement and facilitate effective skill development. It harnesses the advantages of Robot-Assisted Therapies (RATs) by employing robot avatars and integrating them with Computer-Assisted Therapies (CATs) within a web-based solution. The integration of automatic gaze and pose detection algorithms within RoboCA<sup>3</sup>T addresses the challenge posed by potential human error and observation bias in assessing the child's progress, thereby ensuring accurate results. This research responds to the need for more effective, technology driven therapies for autism, filling gaps in existing methods.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Objectives</h3>\\n \\n <p>The primary goal of this research is to create a robot inspired computer assisted adaptive autism therapy that maximises engagement and enhances joint attention and imitation skills.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>The study involves 11 ASD children with 30 sessions (divided into two halves) per module over eight months, comprising 660 experimental trials, 110 familiarizations, and 110 follow-up sessions. The joint attention module evaluates the subject's gaze pattern using WebGazer for gaze detection in response to four least-to-most robot-generated cues. The imitation module utilises robot-generated pose for comparing subjects' imitated actions using Tensorflow Lite for pose estimation.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results and Conclusions</h3>\\n \\n <p>The effectiveness of therapy was substantiated by comparing Childhood Autism Rating Scale (CARS) scores before and after intervention. Significant improvements were noted between the first and second therapy halves, validated by Wilcoxon signed-rank tests (<i>p</i> < 0.01) and spearman's correlation analysis, reinforcing the observed improvements in joint attention and imitation skills.</p>\\n </section>\\n </div>\",\"PeriodicalId\":48071,\"journal\":{\"name\":\"Journal of Computer Assisted Learning\",\"volume\":\"40 5\",\"pages\":\"2031-2048\"},\"PeriodicalIF\":5.1000,\"publicationDate\":\"2024-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computer Assisted Learning\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/jcal.12990\",\"RegionNum\":2,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Assisted Learning","FirstCategoryId":"95","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jcal.12990","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
RoboCA3T: A Robot-Inspired Computer-Assisted adaptive autism therapy for improving joint attention and imitation skills through learning and computing innovations
Background
This study presents a Robot-Inspired Computer-Assisted Adaptive Autism Therapy (RoboCA3T) focusing on improving joint attention and imitation skills of children with autism spectrum disorder (ASD). By harnessing the inherent affinity of children with ASD for robots and technology, RoboCA3T offers a therapeutic environment designed to maximise engagement and facilitate effective skill development. It harnesses the advantages of Robot-Assisted Therapies (RATs) by employing robot avatars and integrating them with Computer-Assisted Therapies (CATs) within a web-based solution. The integration of automatic gaze and pose detection algorithms within RoboCA3T addresses the challenge posed by potential human error and observation bias in assessing the child's progress, thereby ensuring accurate results. This research responds to the need for more effective, technology driven therapies for autism, filling gaps in existing methods.
Objectives
The primary goal of this research is to create a robot inspired computer assisted adaptive autism therapy that maximises engagement and enhances joint attention and imitation skills.
Methods
The study involves 11 ASD children with 30 sessions (divided into two halves) per module over eight months, comprising 660 experimental trials, 110 familiarizations, and 110 follow-up sessions. The joint attention module evaluates the subject's gaze pattern using WebGazer for gaze detection in response to four least-to-most robot-generated cues. The imitation module utilises robot-generated pose for comparing subjects' imitated actions using Tensorflow Lite for pose estimation.
Results and Conclusions
The effectiveness of therapy was substantiated by comparing Childhood Autism Rating Scale (CARS) scores before and after intervention. Significant improvements were noted between the first and second therapy halves, validated by Wilcoxon signed-rank tests (p < 0.01) and spearman's correlation analysis, reinforcing the observed improvements in joint attention and imitation skills.
期刊介绍：
The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope
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